HyPo – Modeling of the laser additive welding process considering the resulting properties of hybrid porous structures

Additive manufacturing processes such as Laser Directed Energy Deposition (L-DED) enable the production of components with locally tailored properties. In particular, hybrid porous structures (HyPo) open up new opportunities for lightweight construction, energy absorption, and functionalization. However, the interactions between process parameters, pore formation, and material properties are complex and not yet fully understood. Experimental investigations are time- and cost-intensive, making a digital approach to process planning and optimization desirable. To date, analysis of process, structure, and properties for a component is not feasible, as a comprehensive process modeling framework is lacking. Consequently, targeted design considering such a process model is not yet possible.

Objectives

The goal of HyPo is to develop a physics-based, multi-scale modeling approach for the L-DED process. At the micro-level, energy input, melt pool formation, and solidification are simulated. These results feed into the feature level to calculate residual stresses and temperature fields. At the component level, virtual material models are derived to predict process-dependent property distributions from the simulation. The project thus enables simulation-driven process design of hybrid porous structures and targeted control of material properties.

Benefits

• Process understanding – prediction of stresses and porosity
• Quality – targeted control of material properties
• Efficiency – reduced experimental effort through simulation
• Innovation – new design freedoms for functional components

Approach

To achieve these objectives, a multi-scale simulation chain is being developed, coupling the micro-, feature-, and component levels. Experimental analyses provide data on melt pool size, temperature fields, and pore formation, which are incorporated into the numerical models and validated through experimental trials. Close coordination between subprojects ensures that the model can describe and capture as many component properties as possible. The results are transferred to the component level to predict property distributions and process limits. The model also enables other subprojects of the Transregional Collaborative Research Center to perform simulation-driven process optimization.

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Contact Mariem Ben Salem via email at bensalem@ifw.uni-hannover.de  or by phone at +49 511 762 18305.